Agents mostly don't run ML/AI code; they're a structured loop around LLM calls and exist mostly to give an LLM access to local tools in some application domain; think "reading my email for me" rather than "driving ML systems".
That doesn't negate what OP was saying at all, the better support in Python isn't for "running ML/AI code" but in things like agent frameworks, observability tools, SDKs, etc. None of which directly run AI code but are still helpful/necessary and for the most part better represented (and supported) in the Python world, although that seems like it's slowly changing.
There are agent frameworks in most languages at this point so the question just comes down to "can you invoke tools for the problem you want to solve in that language". Yes, Python is really great at that. So is Go and Javascript.
I think I'd condense this out to "this is not a really important deciding factor in what language you choose for your agent". If you know you need something you can only get in Python, you'll write the agent in Python.
